Costs and benefits of the mixed-mating system of<i>Narcissus serotinus</i>(Amaryllidaceae) in the conservation of small fragmented populations
Bibliographic record
Abstract
Small fragmented populations often exhibit reduced plant–pollinator interactions and scarce outcrossing opportunities. In this context, mixed-mating systems can be advantageous since selfing can provide reproductive assurance, but they may also carry relevant costs such as those involved in inbreeding depression. This study examines the advantages and costs of selfing in Narcissus serotinus L., a mixed-mating geophyte that currently occurs in several fragmented populations in Portugal, that resulted from the construction of the largest European dam. Observation of pollinators revealed that cross-pollination is less frequent in small than in large populations. Manual self-pollinations significantly increased fruit and seed set in small-size populations, also suggesting limited insect pollination. The existence of selfing may provide reproductive assurance in small-size populations of N. serotinus where outcrossing pollination is reduced. Although floral biology and experimental pollinations showed that N. serotinus is capable of autonomous selfing, four of the six fitness traits studied showed significant inbreeding depression in all populations. The high levels of inbreeding depression found in N. serotinus suggest that the initial reproductive assurance advantage of selfing may be counterbalanced by lower survival of the resulting individuals and a decrease in the evolutionary potential of the populations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".